ArticleWorld journal of surgery2026
Data Harmonization for Collaborative Research Among Australian and US Registries: A Case Study in Medullary Thyroid Cancer (MTC).
Article in World journal of surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Data Harmonization for Collaborative Research Among Australian and US Registries: A Case Study in Medullary Thyroid Cancer (MTC).World journal of surgery · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMedullary thyroid cancer (MTC) is a neuroendocrine tumor comprising approximately 1%-2% of all thyroid malignancies. The rarity and more aggressive biology of MTC requires robust sample sizes to enhance our understanding of this complex disease. Harmonization is the process of standardizing raw data from multiple sources, by resolving differences in format and terminology, to create a unified dataset that can be analyzed for a common purpose. The aim of this project was to assess the feasibility of collaboration, data mapping, and harmonization among clinical sites investigating MTC internationally.
methodsThe Maelstrom guidelines were used to perform retrospective data harmonization from three clinical networks in Australia and the Unites States for adult patients with MTC, between 2018 and 2021. Data received were categorized as an exact, close, or low match. Exact and close matches were combined to form a harmonized dataset. A logistic regression analysis was then performed to determine pre-operative factors associated with the presence of cervical lymph node metastases.
resultsData were received from three separate clinical networks. This comprised 114 patients, 17 hospitals and 4674 data points. The completeness of data received ranged from 57.4% to 97.3%. Overall, 80.8% of data received were suitable for harmonization including basic demographics, basis of diagnosis, genetic testing (but not results), select clinical findings, pre-operative investigations, operative details, histopathology, and TNM staging. The prevalence of palpable lymph node involvement at presentation in the harmonized dataset was 15.8%. Younger patients (less than 55 years) and patients with abnormal nodes on ultrasound were strongly associated with cervical lymph node metastases. Conversely, patients with an incidental diagnosis of MTC had markedly lower odds of presenting with cervical lymph node metastases.
conclusionData mapping and harmonization across national and international sites is feasible and enables meaningful modeling that would not be possible with individual datasets. The Maelstrom guidelines provide a useful template regarding how to achieve this efficiently. This manuscript is a white paper for clinicians and researchers studying rare diseases, such as MTC, regarding how to share heterogeneous raw data and collaborate with other clinical sites.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.